Sanitation improvement is crucial in saving lives that are lost due to water contamination. Progress towards achieving full sanitation coverage is still slow in low-income informal settlements in most developing countries. Furthermore, resources are being wasted on installing facilities that are later misused or never used because they do not meet the local demand. Understanding demand for impr...

We develop the first approximation algorithms with worst-case performance guarantees for periodic-review perishable inventory systems with general product lifetime, for both backlogging and lost-sales models. The demand process can be non-stationary and correlated over time, capturing such features as demand seasonality and forecast updates. The optimal control policy for such systems is notori...

One of the most important policies adopted in inventory control is the (R,S) policy (also known as the “replenishment cycle” policy). Under the non-stationary demand assumption the (R,S) policy takes the form (Rn,Sn) where Rn denotes the length of the n th replenishment cycle, and Sn the corresponding order-up-to-level. Such a policy provides an effective means of damping planning instability a...

Risks have recently emerged as a key issue for the life cycle of a supply chain. Operations risks are particularly important because of the propagation of their effects. An ARIMA model of a supply chain is proposed to represent flow dynamics in a network of enterprises and their responses to strong disturbances from the demand and/or the offer side. When the amplitude of product flows variation...

Do greater potential gains from trade enhance or erode contracting institutions? In an anonymous exchange environment traders can sign a contract, hence agreeing to interact with the assigned partner, or wait till the next match. Any contract can be endorsed (for a pay) by the enforcement agency, which then observes the interaction with a positive probability known to the traders and punishes t...

Customers and downstream supply chain partners often place, or can be induced to place, orders in advance of future requirements. We show how to optimally incorporate advance demand information into periodic-review, multiechelon, inventory systems in series. While the state space for series systems appears to be formidably large, we decompose the problem across locations, as in Clark and Scarf ...

Corollary 4. Suppose that a) the discrepancies t are independent over time and the distribution Ht is stationary and such that Pr{ t > 0} ≥Pr{ t < 0} (and Pr{ t = 0}< 1), b) demand follows a newsvendor distribution with known g() and unknown parameter θ > 0, on which the sellers share a non-degenerate prior distribution with well-defined density, and c) the naive and tracking sellers stock the ...

Under stochastic demand and deterministic processing times, we discussed a single-part JIT production system with the production-ordering and supplier Kanbans and derived the stationary distributions of the backlogged demand. In this paper, we extend the system to a multi-part JIT production system, deterministic processing times and withdrawals with lead time. These conditions are more realist...

A central question in designing server farms today is how to efficiently provision the number of serversto handle unpredictable demand patterns, so as to extract the best performance while not wastingenergy. While one would like to turn servers off when they become idle to save energy, the largesetup cost (both, in terms of setup time and energy penalty) needed to switch the server ...

Forecasting short-term heat demand is an integral function of district energy management applications. Although some well-known methods, such as support vector machine and artificial neural networks, can be employed, most them require additional variables (such temperature humidity) in addition to the itself order make accurate prediction. In this paper, a differencing-convolutional network-lon...